How to use Artificial Intelligence – A guide for everyone! Course Syllabus

Overview: This beginner-friendly course provides a clear, non-technical introduction to artificial intelligence, designed for professionals across industries. Over approximately 5 hours of engaging content, you'll gain a solid understanding of core AI concepts, workflows, tools, and ethical considerations. With jargon-free explanations and real-world examples, the course builds from fundamentals to applications, enabling you to confidently engage with AI initiatives in your role. No coding experience is required—just curiosity and a desire to understand AI’s potential and limitations.

Module 1: Introduction to AI Fundamentals

Estimated time: 0.5 hours

• Defining AI, machine learning, and deep learning
• Historical evolution of artificial intelligence
• Overview of key AI subdomains
• Essential terminology explained in simple terms

Module 2: The AI Development Workflow

Estimated time: 0.75 hours

• Data collection and preprocessing basics
• Training, validation, and testing phases
• Model evaluation using performance metrics
• Understanding deployment challenges

Module 3: Machine Learning Techniques

Estimated time: 1 hour

• Supervised learning: linear regression, decision trees, SVM
• Unsupervised learning: clustering with k-means
• Dimensionality reduction using PCA
• Practical use cases for each method

Module 4: Deep Learning & Neural Networks

Estimated time: 1 hour

• Neural network architecture and components
• Activation functions and backpropagation
• Convolutional Neural Networks (CNNs) for images
• Recurrent Neural Networks (RNNs) for sequences

Module 5: AI Tools & Platforms Overview

Estimated time: 0.75 hours

• High-level overview of TensorFlow and Keras
• Introduction to PyTorch and Google Cloud AI
• Using AutoML and no-code AI APIs
• Accessing NLP, vision, and speech tools

Module 6: Real-World Applications & Case Studies

Estimated time: 0.75 hours

• AI in healthcare diagnostics
• Fraud detection in finance
• Recommendation engines and chatbots
• Business impact and ROI analysis

Module 7: Responsible AI & Ethics

Estimated time: 0.5 hours

• Identifying bias in AI systems
• Strategies for bias mitigation
• Privacy, transparency, and regulations
• Responsible AI frameworks

Module 8: Next Steps & Career Pathways

Estimated time: 0.5 hours

• Building an AI portfolio with sample projects
• Getting started on Kaggle
• Recommended learning paths and certifications
• AI career opportunities for non-technical roles

Prerequisites

• No prior technical or coding experience required
• Basic computer literacy
• Interest in AI applications across industries

What You'll Be Able to Do After

• Explain core AI concepts clearly to non-technical stakeholders
• Evaluate AI tools and platforms for business use
• Understand the stages of AI model development
• Identify real-world applications of AI in your industry
• Apply ethical guidelines to promote responsible AI adoption